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Enregistrement W1588239581 · doi:10.14264/158129

Acquisition of word order in Chinese as a foreign language: An error taxonomy

2006· dissertation· en· W1588239581 sur OpenAlex

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Notice bibliographique

RevueThe University of Queensland · 2006
Typedissertation
Langueen
DomaineComputer Science
ThématiqueText Readability and Simplification
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWord orderLinguisticsSecond-language acquisitionComputer scienceSentenceNatural language processingVerbChinese as a foreign languageForeign languageTaxonomy (biology)Artificial intelligence

Résumé

récupéré en direct d'OpenAlex

Research in the field of Chinese second/foreign language (L2) acquisition, at present, does not match the increasing demand to learn Chinese as an L2, given that Chinese is the fastest growing foreign language (FL) in countries such as Japan, South Korea, the United States, Canada and Australia. There is a significant gap between Chinese L2 acquisition research and the large body of literature in second language acquisition (SLA), which mainly focuses on English L2. The need for more research in Chinese SLA is compelling.Particularly, research in Chinese L2 word order acquisition requires more attention because word order plays a more complex role in Chinese than in English. Chinese relies heavily on word order for information structuring of a sentence because this language lacks other means, such as verb endings indicating tense and aspect, to accomplish this function. Due to the different roles word order plays in Chinese and English, adult English-speaking learners find Chinese word order acquisition very challenging. Chinese L2 word order errors frequently occur in learners' L2 production. However, Chinese L2 researchers and teachers are left with no means to adequately describe and explain these errors for instruction purposes. This dissertation develops such a means -- a comprehensive taxonomy of Chinese L2 word order errors. This taxonomy organizes these errors into a logical system of classification. Through the classification, explicit description of various Chinese L2 word order errors is achieved, and specific sources of these errors are traced.Data was collected from 116 native-English-speaking learners of Chinese at a large university in Australia. The Chinese L2 learners were divided into three proficiency levels based on their institutional status. Four hundred and eight word order errors were extracted by qualitatively analyzing the learners’ written samples. Among the 408 word order errors, 404 (99%) are successfully classified into different categories according to a new criterion proposed in this dissertation.The new taxonomy provides a principle-based description and explanation of various Chinese L2 word order errors. A word order error is deemed to constitute an error when it violates a relevant word order principle (or sub-principle). These principles not only explain why an error is an error but also provide a means for correcting the error. In a pedagogical sense, the directness and explicitness in explaining word order errors achieved by employing this taxonomy cannot be achieved by relying on any other sources of errors available in the literature.The new taxonomy overcomes the limitations of existing taxonomies in the literature that are either superficial, or unsystematic, or not empirically testable. For example, it draws on the Cognitive Functionalist Approach of L2 acquisition. Both its description and explanation of Chinese L2 word errors go beyond superficiality. The approach maintains that adult L2 learners' conceptualization of the world is initially based on their L1. Their conceptualization of the world imposes constraints on the linguistic structures of their L2. Therefore, errors may occur when English learners of Chinese impose their conceptualization based on the English language onto the Chinese structures. The new taxonomy is systematic because it categorizes word order errors using one criterion. New categories emerging from the data and the existing categories from the literature are incorporated into one system. Finally, the new taxonomy is empirically testable because many new categories emerged from the data. It is an open-ended rather than a closed system. New categories can be added as necessary.The dissertation finds that violation of relevant word order principles has a high explanatory value for the various word order errors encountered in the data. This has clear pedagogical implications. Chinese L2 learners generally lack awareness of the word order principles (and sub-principles) on which the new taxonomy is based. These principles and sub-principles are seen to be of considerable importance to the acquisition of Chinese L2 word order. In order to improve learners' word order performance, the results of this study indicate that it is imperative for the basic Chinese word order principles be included in a CFL curriculum.

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Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,791
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,011
Tête enseignante GPT0,238
Écart entre enseignants0,227 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle